Different Scales Of Analysis Research Articles

Grid_strain and grid_strain3: Software packages for strain field computation in 2D and 3D environments

Two Matlab™ software packages for strain field computation, starting from displacements of experimental points (EPs), are here presented. In particular, grid_strain estimates the strain on the nodes of a regular planar grid, whereas grid_strain3 operates on the points of a digital terrain model (DTM). In both cases, the computations are performed in a modified least-square approach, emphasizing the effects of nearest points. This approach allows users to operate at different scales of analysis by introducing a scale factor to reduce or also exclude points too far from grid nodes. The input data are displacements (or velocities) that can be provided by several techniques (e.g. GPS, total topographical station, terrestrial laser scanner). The analysis can be applied to both regional- and local-scale phenomena, to study tectonic crustal deformations (strain ≈10 −8−10 −6) or rapid landslide collapses (10 −4−10 2), and to characterize the kinematics of the studied system. Errors on strains and geometric significance of the results are also provided.

Using regression trees to predict alpha diversity based upon geographical and habitat characteristics

Different environmental factors act as driving forces of diversity at different scales of analysis; and also the effect of one environmental factor changes as the scale of analysis changes. Most studies rely on multiple regression models, and such models tend to mix-up the effect of all factors and assume that factors effects are additive. We believe that the effect of environment on diversity should be characterized by a hierarchical structure with coarse scale factors, like geographical tropics to poles gradients, defining the envelope of possible diversity conditions, and other more local factors, like habitat structure, being responsible for the fine tuning of diversity. This structure is most efficiently modeled with regression trees. We show that for six habitat types in Greek protected areas regression tree models were able to describe plant species richness based upon environmental factors considerably more efficiently than multiple regression models. More importantly when the models were extrapolated to other sites in Greece, outside their domain, the differences between the predictive ability of the two approaches was magnified. The tree models picked up important ecological characteristics, and a hierarchical structure that used coarse scale factors, like latitude and longitude, for the coarse scale estimate of alpha diversity, and finer scale factors like fragmentation, for the fine-tuning of the estimation. Therefore, we advocate that the regression tree methodology is most appropriate for modeling the relationship between diversity and environmental factors, and the use of the classical regression approaches might be misleading.

Coastal sea level trends from TOPEX-Poseidon satellite altimetry and tide gauge data in the Mediterranean Sea during the 1990s

A joint analysis of TOPEX-Poseidon satellite altimetry and tide gauge data is used to estimate sea level trends along the Mediterranean Sea coast from 1993 January to 2002 February. A generalized least squares (GLS) method allows us to take into account the space-time distribution of the data and their respective error budgets. Nearly optimal parameters of the covariance functions involved in the GLS method are estimated at different scales of analysis, using a trial and error method. Combined data time series are then reconstructed at 153 locations along the coast. The basin-wide averaged linear trend for the coastal area shows a sea level rise of 4.54 ± 0.30 mm yr −1 compared to 4.28 ± 0.30 mm yr −1 for the open ocean only, i.e. a 0.26 ± 0.16 mm yr −1 difference (the error is smaller because the systematic error does not take part in the error budget) which is quite significant. At local scales, the coastal linear trends ranges from −8.5 to +13.5 mm yr −1 which is much narrower than ranges found by other open sea studies ([−24.0 to −10.0; +16.0 to +29.0] mm yr −1 ). However, a detailed error budget shows that the largest estimation errors come from the spatial extrapolation of the sea level signal required when tide gauge and altimeter data are merged. The second error source is the instrumental noise and the random noise generated by the littoral contamination on altimeter measurements and from the crustal motions that are contaminating the tide gauge signal. At local scale, it is estimated that 85 percent of the error on linear trends does not exceed 2 mm yr −1 .

Uncertainty in adaptive capacity and the importance of scale

Understanding different adaptive capacities is a prerequisite for targeting interventions to reduce the adverse impacts of climate change. Indicators and indices are common tools in this process, but their construction embodies many uncertainties, not least of which is their scale specificity. This paper describes the development of two empirical adaptive capacity indices for use at different scales of analysis: a national index for cross-country comparison in Africa and a household index for cross-household comparison in a village in Limpopo province, South Africa. Explaining the decisions made at each stage of construction illuminates the degree of uncertainty involved when assessing adaptive capacity, and how this uncertainty is compounded when looking across different scales of analysis. It concludes that the central elements of adaptive capacity, based on institutional collective response and the availability of and access to resources, are common at different scales, although the structure of each index is scale-specific. Hence the findings of these apparently irreconcilable scales of analysis converge to demonstrate points of leverage for policy intervention to raise resilience and the capacity to adapt to the risks posed by climate change.

Enhancing retail location decision support: The development and application of geovisualization

Geovisualization refers to the visual exploration, analysis, synthesis and presentation of geospatial data. This paper presents findings from research that has focused on developing and applying geovisualization techniques and technologies for use within retail location decision support. To date, retailers represent a major user group of geographic information system (GIS) -based decision support technologies, with applications ranging from trade area mapping to store portfolio planning. However, the ability to handle spatial–temporal data, visualize change, and explore the temporal dimension of spatial data is limited within conventional GIS. The paper details the development of a prototype geovisualization system that has been designed to enable visualization of spatial–temporal change of retail-related data. From this explicitly visual paradigm, a number of examples of potential analysis are examined at four different scales of analysis: national, regional, market and micro-level. The paper highlights both the challenges and potential to enhance retail decision support by integrating geovisualization techniques and technology within decision support activities.

Enabling Innovation: Technology- and System-Level Approaches that Capitalize on Complexity

we finish our training most of us believe that it is our job to conceptualize designs, develop products and worry little about what happens after they have been introduced. Our courses are generally too practical to bother with theories about how innovation occurs, who it affects and how we might better manage the process. Diesel, inventor of the diesel engine, distinguished between two phases in technological progress: the conception and carrying out of the idea, which is a happy period of creative mental work in which technical challenges are overcome, and the introduction of the innovation, which is a “struggle against stupidity and envy, apathy and evil, secret opposition and open conflict of interests, a horrible period of struggle with man, a martyrdom even if success ensues.” Diesel is perhaps overstating the difficulties of managing innovation, but nevertheless as engineers we are still taught to prefer technical “invention” and leave dealing with people and the “innovation” side to others. However, engineers ignore the innovation process at their peril. Enabling innovation means building on peoples’ ingenuity and motivations, rather than working against them. In this paper I describe the learning selection approach to enabling innovation that capitalizes on the complexity of social systems at different scales of analysis. In the first part of the paper I describe the approach and how it can be used to guide the early stages of setting up a “grassroots” innovation process. In the second part of the paper I look at how the learn selection model can be used “top-down” to guide research investments to trigger large-scale systemic change.

Spatial Integration at Multiple Scales: Rice Markets in Madagascar

This paper uses an exceptionally rich data set to test the extent to which markets in Madagascar are integrated across space at different scales of analysis and to explain some of the factors that limit spatial arbitrage and price equalization within a single country. We use rice price data across four quarters of 2000-2001 along with data on transportation costs and infrastructure availability for nearly 1400 communes in Madagascar to examine the extent of market integration at three different spatial scales - sub-regional, regional, and national - and to determine whether non-integration is due to high transfer costs or lack of competition. The results indicate that markets are fairly well integrated at the sub-regional level and that factors such as high crime rates, remoteness, and lack of information are among the factors limiting competition.

Multi-scale sustainability evaluation of natural resource management systems: Quantifying indicators for different scales of analysis and their trade-offs using linear programming

The purposes of this paper are: (a) to describe a framework designed for multi-scale sustainability evaluation of Natural Resource Management Systems (NRMS), and (b) to illustrate its application for quantitative analysis using linear programming. The framework described here is intended to contribute to the operationalisation of the concept of sustainability by supporting the processes of design, evaluation and implementation of alternative NRMS at different scales. In this paper, Linear Programming is used for the quantitative analysis of indicators and their trade-offs; using a schematised example, the basic characteristics of the Multi-scale Multiple Goal Linear Programming (M-MGLP) method are described. In M-MGLP, indicators pertaining to different scales of analysis can be set as objectives or constraints for the optimisation. In this way, stakeholders interacting in a specific region can be made aware of the consequences of alternative NRMS in terms of the different indicators at the same scale and/or for indicators at other scales of analysis. The paper ends with a discussion of the main strengths and limitations of the framework and, specifically, of linear programming.

Regulars and “Irregulars”: British and Provincial Variability among Eighteenth-Century Military Frontiers

Historical studies have detailed the joint service of provincial and British regular soldiers during the Seven Years’ War (ca. 1754–1763) in colonial North America. The complex relations between these communities and their effect on the material record of military settlements, however, have not been fully addressed within historical archaeology. An analysis of British and provincial domestic structures at New York military sites employing lead shot and ceramic data reveals small-scale material variation between these two groups. The effect that different scales of analysis will have on the nature of this variation is recognized, and a preliminary spatial model of provincial-British relations is developed. The model assumes significant distinctions will characterize small-scale provincial and British contexts, while larger frames of reference may demonstrate similar or conflicting material patterns based on the historical relationship between the two communities. The context for this analysis is informed by recent critiques of large-scale core/periphery perspectives in the archaeology of frontier settlements.

Exploring diversity in soil fertility management of smallholder farms in western Kenya

Abstract The processes of nutrient depletion and soil degradation that limit productivity of smallholder African farms are spatially heterogeneous. Causes of variability in soil fertility management at different scales of analysis are both biophysical and socio-economic. Such heterogeneity is categorised in this study, which quantifies its impact on nutrient flows and soil fertility status at region and farm scales, as a first step in identifying spatial and temporal niches for targeting of soil fertility management strategies and technologies. Transects for soil profile observation, participatory rural appraisal techniques and classical soil sampling and chemical analysis were sampled across 60 farms in three sub-locations (Emuhaia, Shinyalu, Aludeka), which together represent much of the variability found in the highlands of western Kenya. Five representative farm types were identified using socio-economic information and considering production activities, household objectives and the main constraints faced by farmers. Soil fertility management and nutrient resource flows were studied for each farm type and related to differences in soil fertility status at farm scale. Farm types 1 and 2 were the wealthiest; the former relied on off-farm income and farmed small pieces of land (0.6–1.1 ha) while the latter farmed relatively large land areas (1.6–3.8 ha) mainly with cash crops. The poorest farm type 5 also farmed small pieces of land (0.4–1.0 ha) but relied on low wages derived from working for wealthier farmers. Both farm types 1 and 5 relied on off-farm earnings and sold the least amounts of farm produce to the market, though the magnitude of their cash, labour and nutrient flows was contrasting. Farms of types 3 and 4 were intermediate in size and wealth, and represented different crop production strategies for self-consumption and the market. Average grain yields fluctuated around 1 t ha−1 year−1 for all farm types and sub-locations. Grain production by farms of types 4 and 5 was much below annual family requirements, estimated at 170 kg person−1 year−1. Household wealth and production orientation affected the pattern of resource flow at farm scale. In the land-constrained farms of type 1, mineral fertilisers were often used more intensively (ca. 50 kg ha−1), though with varying application rates (14–92 kg ha−1). The use of animal manure in such small farms (e.g. 2.2 t year−1) represented intensities of use of up to 8 t ha−1, and a net accumulation of C and macronutrients brought into the farm by livestock. In farms of type 5, intensities of use of mineral and organic fertilisers ranged between 0–12 kg ha−1 and 0–0.5 t ha−1, respectively. A consistent trend of decreasing input use from farm types 1–5 was generally observed, but nutrient resources and land management practices (e.g. fallow) differed enormously between sub-locations. Inputs of nutrients were almost nil in Aludeka farms. Both inherent soil properties and management explained the variability found in soil fertility status. Texture explained the variation observed in soil C and related total N between sub-locations, whereas P availability varied mainly between farm types as affected by input use.

Molecular diversity and biomass of epilithic biofilms from intertidal rocky shores in the Gulf of Mexico

Epilithic biofilms play key roles in rocky shore ecosystems. The diversity and biomass of epilithic biofilms were determined along a subtropical intertidal rocky shore at Xpicob, Southern Gulf of Mexico (Campeche, Mexico). Biofilm diversity was assessed by polymerase chain reaction (PCR) amplification of partial 16 S rRNA genes using single-strand conformation polymorphism (SSCP). Triplicate 2 cm×2 cm biofilm samples per site were taken randomly from 0.6 m×0.6 m quadrats located in two sampling sites, established 20 m apart within a homogeneous calcareous intertidal platform. Twenty-two partial rRNA sequences, belonging to four bacterial divisions (Cyanobacteria, Bacteroidetes, Actinobacteria and Proteobacteria), were recovered from these biofilms; of these, cyanobacteria were the most abundant (41%). The occurrence of cyanobacterial sequences in most samples, along with the detection of high levels of chlorophyll a and phycobiliprotein, indicates that these organisms are dominant within the biofilms. Consistent with previous reports, thick-sheathed cyanobacteria such as those found in this study (Xenococcus, Myxosarcina and Chroococcidiopsis) are typical in habitats in intertidal zones. In addition, most of the detected organisms from other bacterial lineages had closest relatives displaying biofilm phenotypes that suggested stressful conditions (i.e. desiccation) prevailed in the intertidal shores; this was selecting for biofilm-forming or thick-sheathed organisms as an ecological adaptation to withstand the conditions. Unweighted pair-group method with arithmetic mean (UPGMA) analysis of SSCP profiles indicated that there was significant spatial heterogeneity in biofilm community composition across different scales of analysis and that this heterogeneity was related to the distance at which samples were taken. This analysis showed that certain organisms appeared to be station specific and that the biofilm community structure varied even on a small scale (1 cm). Since no significant differences in bulk sea water or substratum physicochemistry were observed, these results suggest that small-scale variability of environmental conditions, surface properties and/or biological interactions (i.e. allelopathy) may be important factors structuring these biofilm communities.

A Scale‐Sensitive Test of Attraction and Repulsion Between Spatial Point Patterns

There exist a variety of tests for attraction and repulsion effects between spatial point populations, most notably those involving either nearest‐neighbor or cell‐count statistics. Diggle and Cox (1981) showed that for the nearest‐neighbor approach, a powerful test could be constructed using Kendall's rank correlation coefficient. In the present paper, this approach is extended to cell‐count statistics in a manner paralleling the K‐function approach of Lotwick and Silverman (1982). The advantage of the present test is that, unlike nearest‐neighbors, one can identify the spatial scales at which repulsion or attraction are most significant. In addition, it avoids the torus‐wrapping restrictions implicit in the Monte Carlo testing procedure of Lotwick and Silverman. Examples are developed to show that this testing procedure can in fact identify both attraction and repulsion between the same pair of point populations at different scales of analysis.

An Inventory-Based Approach to Landslide Susceptibility Assessment and its Application to the Virginio River Basin, Italy

An inventory-based method for the assessment of landslide susceptibility is presented in this article. The method has been tested in the Virginio River Basin, a tributary of the Arno River whose confluence is located about 20 km downstream from Florence (Italy). The scope of this study includes setting up a procedure for landslide hazard zoning to be applied by those urban planners typically working on small areas at large scale. The proposed method deals with traditional and well-known landslide hazard analyses, based on geomorphological tools, and its most original contribution is represented by the attempt to carry out and apply a technique for landslide hazard assessment that takes into account two different scales of analysis. The basis of a detailed landslide inventory and the first phase of this research was an in-depth geomorphological investigation at basin scale (1:25,000–1:10,000). This was aimed at indicating the most important factors influencing the landslide processes within the area, which also turned out to be the most generally accepted factors: a) slope gradient in which the landslide originated, b) lithology, and c) land cover. Once those factors were defined as thematic vector data, they were expressed using GIS overlay mapping, allowing the identification, for the entire Virginio River basin, of first-order homogeneous domains (Unique Condition Units, UCUs) that contain, for each landslide type, unique combinations (domains) of the selected hillslope stability factors. The domains are the basic Terrain Units for the subsequent landslide susceptibility assessment and mapping, which was carried out at slope scale (1:10,000–1:2,000). Landslide factors not identified in the first phase of analysis, but considered to have played an important role in contributing to the activation of the mass movements, so-called second-order landslide preparatory factors, have been taken into account in the second phase of the analysis. Once mapped and spatially referenced, these factors were overlain by vector-based GIS techniques to define second-order UCUs which, in turn, constituted the basis of a landslide susceptibility function. Essentially, this is a logic function based on the presence/absence of preparatory factors and slope instability indicators within previously selected Unique Condition Terrain Units. The final mapping of the areas characterized by different landslide susceptibility levels was performed by vector- and raster-based GIS techniques on the basis of the number and rank of the preparatory factors. The final landslide susceptibility classes, defined by a logical and easily replicable procedure, are considered to be useful in the decision-making procedures associated with territorial planning.

Retailing Revolution in the Eighteenth Century? Evidence from North-West England

This article explores the extent and nature of retail change in the eighteenth century. In focusing on a single region, it places retailing in its spatial, economic and social context; by adopting different scales of analysis – shop, town and region – it reveals much about the spatiality of retailing. The study shows that retail change had penetrated all aspects of retailing and all parts of the regional urban hierarchy by the end of the eighteenth century. However, any retailing revolution was a patchy and conditional process: the pace of change varied, and the gap between large and small towns apparently widened in the early nineteenth century.

Reflections on the “Old” Economy, “New” Economy, and Services

ABSTRACT Economic competitiveness now has less to do with new materials than with new ways of producing, utilizing, and combining diverse knowledges. It is branded as symptomatic of a “new” economy and is often juxtaposed against the “old” economy. As accelerating technological change has greatly increased the volume and quality of the information available to organizations, to firms, and to individual employees, it is asserted that the economy has become more “new” than “old.” But this is predicated on the assumption that there is a “new” economy and that it is somehow distinguishable from the “old.” This paper explores the basis for this dichotomy and whether it really adds anything to understanding contemporary economies and their ongoing development. It will be argued that it is more useful and constructive to examine the economy through a lens dominated by service industries that are now the key drivers of change (innovation, competition, employment) and development. The paper is concluded with a discussion of some items that could usefully be part of an agenda for further research by economic geographers on the evolving spatial and structural attributes of service work and organizations and their impact on cities or regions at different scales of analysis.

The Political Ecology of Land-Use Change: Affluent Ranchers and Destitute Farmers in the Mexican Municipio of Alamos

This paper examines the interactions between the environment political and economic policies and changes in land use and land quality by focusing on one region in northwest Mexico where dramatic transformations have occurred since the early 1970s. A political ecology approach is used to examine the nature and causes of environmental change at different scales of analysis to address the importance of meanings assigned to ecological systems and the effect of human-environmental interactions on natural resources. The objective of the study is to uncover the different circumstances under which farmers and ranchers have affected environmental change and how land-use decisions interact with political economic and environmental drivers through history. An emphasis is placed on the complexity of interactions between drivers and on understanding differences in perspectives between large-scale commercial ranchers more diversified small-scale farmers and ejidatarios bureaucrats and environmentalists. The study concludes that strategies for reducing deforestation and developing reasonable community based plans that promote sustainable livelihoods must consider the local and external causes of deforestation the difficulty of environmental monitoring and intraregional differences in environmental and socioeconomic parameters. (authors)

Response of vertebrates to fenceline contrasts in grazing intensity in semi‐arid woodlands of eastern Australia

Abstract Changes in the abundance, species richness and assemblage composition of vertebrates due to grazing by domestic stock were investigated in the semi‐arid woodlands of eastern Australia. Analyses were based on the differences found at 10 fenceline contrast sites. Two species of amphibians, 22 species of reptiles and two species of small mammal were captured in pit traps during the surveys. Kangaroos (red and eastern grey), sheep, goats and 66 species of birds were recorded along line transects. Analyses revealed that abundance of diurnal reptiles and species richness of diurnal reptiles and birds were significantly lower on heavily grazed sites than they were on lightly grazed sites. At a local scale, the gecko, Gehyra variegata, was more abundant where grazing was heavier, while Diplodactylus conspicillatus, Diplodactylus steindachneri and Rhynchoedura ornata responded to variables indirectly related to grazing intensity (kangaroo density, sheep and goat dung mass and sheep density, respectively). Birds more commonly sighted on lightly grazed areas than heavily grazed areas were the apostlebird, brown treecreeper, crested bellbird, grey butcherbird, hooded robin, jacky winter, little woodswallow, Australian magpie‐lark, mulga parrot, splendid wren, white‐browed treecreeper and yellow‐rumped thornbill. Birds more commonly sighted on heavily grazed areas than on lightly grazed areas were the Australian raven and chestnut‐crowned babbler. Most variation in species composition between sites was due to spatial separation and no regional‐level indicator species of grazing were evident. A combination of direct grazing‐related changes (e.g. loss of ground cover) and indirect effects of the pastoral industry (e.g. introduction of artificial sources of water) lead to changes in fauna at different scales of analysis across regions.

Archaeologies of Recent Rural Sicily and Sardinia: A Comparative Approach

Although there have been increasing amounts of archaeological work carried out in the Mediterranean on Post-Medieval periods, particularly in Greece, historical archaeology in the Anglo-American sense is so far poorly developed in Italy. For many, work on this period is seen as synonymous with the archaeology of capitalism and the growth of world systems. Such concerns require many different scales of analysis and an inter-disciplinary approach. One crucial question for archaeologists is how processes at different scales and perhaps different tempos articulate. While fieldwork typically contributes to the local and regional, the archaeological search for broader syntheses often privileges ecological conditions as determining the nature of possible responses; historians and anthropologists, for their part, have tended to emphasize the economic. Here we present two case studies from broadly ecologically similar areas, the central highlands of Sicily and Sardinia, both with rich archaeological, historical and ethnographic archives from the last two centuries. Our analysis supports work elsewhere in the Mediterranean which suggests that even under the homogenizing influences of global trade and regional ecologies, the specific sociopolitical conditions within which communities and classes articulate with wider forces are crucial in determining historical and cultural trajectories.

Different scales of analysis in classifying streams: from a multimetric towards an integrate system approach.

Two different approaches to define the ecological status of several catchments in NW Portugal are compared. At a coarser scale, whole stream networks were classified using GIS according to variables related to: a) biotic indicators (native and exotic fish species, benthic biotic index and characteristics of the riparian corridor); b) chemical indicators of contamination (industrial and urban organic loads and water quality). This methodology was preceded by a typological classification, so that ecological status could be determined separately for each of the physical units within a watercourse. At a lower scale, sites were categorized on the basis of the invertebrate fauna and the most relevant metrics were selected through multivariate procedures. These two methods can be seen as complementary and they produced similar indications of disturbance levels in spite of different assessment techniques and distinct space scales of analysis. Using the first method (assisted by GIS), we can identify the main typological gradients and the location of the most pristine segments. Relaying on the classification displayed by this method at the catchment scale, the second method one enables us to define with accuracy the sampling sites and the most convenient metrics for biomonitoring in river health assessment systems.

Density–distribution relationships in British butterflies. I. The effect of mobility and spatial scale

Summary Positive relationships between the density and distribution of species in taxonomic assemblages are well documented, but the underlying mechanisms remain poorly understood. Two factors that are expected to be important in explaining variation in these relationships are the spatial scale of analysis and the relative mobility of the study species. We examined density–distribution relationships in British butterflies at a variety of spatial scales. Distributions were proportions of grid squares occupied: 50 m grid within 0·25 km2areas (local), 500 m grid in 35 km2(regional), 10 km grid across England, Wales and Scotland (national), 153 000 km2grid squares across Europe (European), and also seven categories of international distribution (Global; 1 = European endemic to 7 = in 5 + continents). Densities were measured using transect counts at local, regional and national scales. Different relationships between density and distribution occurred at different scales of analysis. When we controlled for the effects of mobility and/or phylogenetic association, a positive relationship between density and distribution was apparent at local, regional and national scales. Species’ national densities in Britain were positively correlated with their European distribution sizes, but significantly negatively correlated with their global range sizes. Butterfly mobility had a positive effect on distribution and a negative effect on density at all spatial scales. For a given total abundance, more mobile species had lower densities but wider distributions, i.e. they were less aggregated than more sedentary species. The decreasing strength of the density–distribution correlation, and the eventual reversal of the pattern, with the increasing magnitude of difference between the scale at which density was measured relative to distribution, suggests that some element of niche may be important in determining densities and distributions. However, the measure of niche breadth analysed did not explain significant variation in density, distribution, or in the density–distribution relationship.